Large-Scale Validation of the Feasibility of GPT-4 as a Proofreading Tool for Head CT Reports.

Background The increasing workload of radiologists can lead to burnout and errors in radiology reports. Large language models, such as OpenAI's GPT-4, hold promise as error revision tools for radiology. Purpose To test the feasibility of GPT-4 use by determining its error detection, reasoning, and revision performance on head CT reports with varying error types and to validate its clinical utility by comparison with human readers.

Explainable vision transformer for automatic visual sleep staging on multimodal PSG signals.

Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.

The Long-Term Immunity of a Microneedle Array Patch of a SARS-CoV-2 S1 Protein Subunit Vaccine Irradiated by Gamma Rays in Mice.

Background/objectives: COVID-19 vaccines effectively prevent severe disease, but unequal distribution, especially in low- and middle-income countries, has led to vaccine-resistant strains. This highlights the urgent need for alternative vaccine platforms that are safe, thermostable, and easy to distribute. This study evaluates the immunogenicity, stability, and scalability of a dissolved microneedle array patch (MAP) delivering the rS1RS09 subunit vaccine, comprising the SARS-CoV-2 S1 monomer and RS09, a TLR-4 agonist peptide.

Deep learning algorithm for predicting left ventricular systolic dysfunction in atrial fibrillation with rapid ventricular response.

Aims: Although evaluation of left ventricular ejection fraction (LVEF) is crucial for deciding the rate control strategy in patients with atrial fibrillation (AF), real-time assessment of LVEF is limited in outpatient settings. We aimed to investigate the performance of artificial intelligence-based algorithms in predicting LV systolic dysfunction (LVSD) in patients with AF and rapid ventricular response (RVR).

Methods And Results: This study is an external validation of a pre-existing deep learning algorithm based on residual neural network architecture.

Automated quantification of cerebral microbleeds in susceptibility-weighted MRI: association with vascular risk factors, white matter hyperintensity burden, and cognitive function.

Background And Purpose: To train and validate a deep learning (DL)-based segmentation model for cerebral microbleeds (CMB) on susceptibility-weighted MRI; and to find associations between CMB, cognitive impairment, and vascular risk factors.

Materials And Methods: Participants in this single-institution retrospective study underwent brain MRI to evaluate cognitive impairment between January-September 2023. For training the DL model, the nnU-Net framework was used without modifications.

Deep Learning Model Using Stool Pictures for Predicting Endoscopic Mucosal Inflammation in Patients With Ulcerative Colitis.

Introduction: Stool characteristics may change depending on the endoscopic activity of ulcerative colitis (UC). We developed a deep learning model using stool photographs of patients with UC (DLSUC) to predict endoscopic mucosal inflammation.

Methods: This was a prospective multicenter study conducted in 6 tertiary referral hospitals.

Ethanol extract from Astilbe chinensis inflorescence suppresses inflammation in macrophages and growth of oral pathogenic bacteria.

Chronic oral inflammation and biofilm-mediated infections drive diseases such as dental caries and periodontitis. This study investigated the anti-inflammatory and antibacterial potential of an ethanol extract from Astilbe chinensis inflorescence (GA-13-6) as a prominent candidate for natural complex substances (NCS) with therapeutic potential. In LPS-stimulated RAW 264.

Discovery of Novel Small Molecule Dual Inhibitor Targeting Toll-Like Receptors 7 and 9.

The aberrant secretion of proinflammatory cytokines by immune cells is the principal cause of inflammatory diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Toll-like receptor 7 (TLR7) and TLR9, sequestered to the endosomal compartment of dendritic cells and macrophages, are closely associated with the initiation and progression of these diseases. Therefore, the development of drugs targeting dysregulated endosomal TLRs is imperative to mitigate systemic inflammation.

Clinical Value of Single-Projection Angiography-Derived FFR in Noninfarct-Related Artery.

Background: The Murray law-based quantitative flow ratio (μFR) is an emerging technique that requires only 1 projection of coronary angiography with similar accuracy to quantitative flow ratio (QFR). However, it has not been validated for the evaluation of noninfarct-related artery (non-IRA) in acute myocardial infarction (AMI) settings. Therefore, our study aimed to evaluate the diagnostic accuracy of μFR and the safety of deferring non-IRA lesions with μFR >0.

IL-7-primed bystander CD8 tumor-infiltrating lymphocytes optimize the antitumor efficacy of T cell engager immunotherapy.

Bispecific T cell engagers (TCEs) show promising clinical efficacy in blood tumors, but their application to solid tumors remains challenging. Here, we show that Fc-fused IL-7 (rhIL-7-hyFc) changes the intratumoral CD8 T cell landscape, enhancing the efficacy of TCE immunotherapy. rhIL-7-hyFc induces a dramatic increase in CD8 tumor-infiltrating lymphocytes (TILs) in various solid tumors, but the majority of these cells are PD-1-negative tumor non-responsive bystander T cells.

Novel Approach for Pancreas Transcriptomics Reveals the Cellular Landscape in Homeostasis and Acute Pancreatitis.

Background & Aims: Acinar cells produce digestive enzymes that impede transcriptomic characterization of the exocrine pancreas. Thus, single-cell RNA-sequencing studies of the pancreas underrepresent acinar cells relative to histological expectations, and a robust approach to capture pancreatic cell responses in disease states is needed. We sought to innovate a method that overcomes these challenges to accelerate study of the pancreas in health and disease.

Thermal-plex: fluidic-free, rapid sequential multiplexed imaging with DNA-encoded thermal channels.

Multiplexed fluorescence imaging is typically limited to three- to five-plex on standard setups. Sequential imaging methods based on iterative labeling and imaging enable practical higher multiplexing, but generally require a complex fluidic setup with several rounds of slow buffer exchange (tens of minutes to an hour for each exchange step). We report the thermal-plex method, which removes complex and slow buffer exchange steps and provides fluidic-free, rapid sequential imaging.

HEG1 Protects Against Atherosclerosis by Regulating Stable Flow-Induced KLF2/4 Expression in Endothelial Cells.

Background: Atherosclerosis preferentially occurs in arterial regions of disturbed blood flow, and stable flow (s-flow) protects against atherosclerosis by incompletely understood mechanisms.

Methods: Our single-cell RNA-sequencing data using the mouse partial carotid ligation model was reanalyzed, which identified Heart-of-glass 1 (HEG1) as an s-flow-induced gene. HEG1 expression was studied by immunostaining, quantitive polymerase chain reaction, hybridization chain reaction, and Western blot in mouse arteries, human aortic endothelial cells (HAECs), and human coronary arteries.

Clinical Benefit of Intravascular Imaging Compared With Conventional Angiography in Left Main Coronary Artery Intervention.

Background: The RENOVATE-COMPLEX-PCI (Randomized Controlled Trial of Intravascular Imaging Guidance Versus Angiography-Guidance on Clinical Outcomes After Complex Percutaneous Coronary Intervention) demonstrated that intravascular imaging-guided percutaneous coronary intervention (PCI) improved clinical outcome compared with angiography-guided PCI for patients with complex coronary artery lesions. This study aims to assess whether the prognostic benefit of intravascular imaging-guided procedural optimization persists in patients undergoing PCI for left main coronary artery disease.

Methods: Of 1639 patients enrolled in the RENOVATE-COMPLEX-PCI, 192 patients with left main coronary artery disease were selected for the current prespecified substudy.

Cancer signature ensemble integrating cfDNA methylation, copy number, and fragmentation facilitates multi-cancer early detection.

Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay.

Neuroprotective Effects of Water Extract from Brown Algae in an Experimental Model of Focal Cerebral Ischemia In Vitro and In Vivo.

Focal cerebral ischemia (fCI) can result in brain injury and sensorimotor deficits. Brown algae are currently garnering scientific attention as potential therapeutic candidates for fCI. This study investigated the therapeutic effects of the hot water extract of (wPB), a brown alga, in in vitro and in vivo models of fCI.

Adaptive design of mRNA-loaded extracellular vesicles for targeted immunotherapy of cancer.

The recent success of mRNA therapeutics against pathogenic infections has increased interest in their use for other human diseases including cancer. However, the precise delivery of the genetic cargo to cells and tissues of interest remains challenging. Here, we show an adaptive strategy that enables the docking of different targeting ligands onto the surface of mRNA-loaded small extracellular vesicles (sEVs).

Hema-seq reveals genomic aberrations in a rare simultaneous occurrence of hematological malignancies.

Co-occurrence of multiple myeloma and acute myelogenous leukemia is rare, with both malignancies often tracing back to multipotent hematopoietic stem cells. Cytogenetic techniques are the established baseline for diagnosis and characterization of complex hematological malignancies. In this study, we develop a workflow called Hema-seq to delineate clonal changes across various hematopoietic lineages through the integration of whole-genome sequencing, copy-number variations, cell morphology, and cytogenetic aberrations.

Association of Neuropsychiatric Symptom Profiles With Cognitive Decline in Patients With Parkinson Disease and Mild Cognitive Impairment.

Background And Objectives: Neuropsychiatric symptoms (NPS) are closely associated with cognitive decline in patients with Parkinson disease (PD). We investigated which profiles of NPS are associated with the risk of dementia in PD with mild cognitive impairment (PD-MCI).

Methods: We retrospectively assessed 338 patients with PD-MCI from a single tertiary hospital, who underwent neuropsychological tests and a neuropsychiatric inventory (NPI) questionnaire.

Parallel shift of DNA methylation and gene expression toward the mean in mouse spleen with aging.

Age-associated DNA-methylation drift (AMD) manifests itself in two ways in mammals: global decrease (hypomethylation) and local increase of DNA methylation (hypermethylation). To comprehend the principle behind this bidirectional AMD, we studied methylation states of spatially clustered CpG dinucleotides in mouse splenic DNA using reduced-representation-bisulfite-sequencing (RRBS). The mean methylation levels of whole CpGs declined with age.